One of the most difficult problems in drug discovery and toxicology is the ability to extrapolate results from early studies at the biochemical and cell-based level to effects in humans. The resulting inefficiencies in this extrapolation result in a high attrition rate in drug development and are an enormous drain of resources, effectively passing the buck on to consumers in one manner or another.
From the pollutants in the air we breathe to side-effects from drugs necessary for our health, we are surrounded by chemicals in our environment. It is important to determine which of these chemicals pose health risks and which are relatively harmless. Over 50,000 chemicals are in need of accurate toxicology assessment (Whittenberger J. Toxicity testing: strategies to determine needs and priorities. Washington D.C.: National Academy Press; 1984; and Kreweski D. Toxicity Testing in the 21st Century: A Vision and a Strategy. 500 Fifth Street, NW Washington, D.C. 20001: National Academy Press; 2007). Understanding the mechanism of action is becoming recognized as a critical parameter for accurate toxicology assessment (Lock et al. Toxicol. Lett. 2003 April; 140-141:317-322.). However, there are limited choices in the marketplace for comprehensive tests to report toxicology pathway activation. The currently available methods are tedious in application or removed from a whole-organism format. As a result, toxicology researchers are in need of fast and efficient high-throughput methods to detect toxicology pathway activation.
Methods using intact cells or whole organisms are challenging to apply in high-throughput formats. Whole organism approaches are the most reliable in capturing accurate correlative toxicity data because the tests are performed in a native-context platform. Yet these approaches are costly for high-throughput implementation with classical models such as the mouse. Tissue must be harvested and either RNA extracted for transcription analysis (microarrays (Shioda J. Environ. Pathol. Toxicol. Oncol 2004; 23 (1):13-31), RNA-seq (Kamb Res. Toxicol. 2011 August; 24 (8):1163-1168.), rtPCR (Walker J. Biochem. Mol. Toxicol. 2001; 15 (3):121-127.)) or metabolic analysis by specific biochemical assay (P450 (Guengerich Chem. Res. Toxicol. 2008 January; 21 (1):70-83) and MDR (Sarkadi Physiol. Rev. 2006 October; 86 (4):1179-1236.) transporter activity). Furthermore, tissue specific toxicity mandates careful dissection to allow accurate capture of toxicology data (such as sedimented-tissue lysates of liver, brain, and other tissues). As a result, intact organism toxicity approaches are difficult to implement in cost effective high-throughput strategies. In vitro analysis on cell culture systems is a method more amenable to high-throughput analysis. The common approach is to transfect primary cultures with reporter plasmids and detect gene activation as increased expression of reporter genes. These platforms are expensive, time consuming to maintain, and can be plagued with reproducibility problems. An additional drawback of cell culture transfection methods is the lack of native context. Frequently cell culture responses can give hypersensitive results and these results disappear upon whole organism analysis. Creation of transgenic immortalized lines can solve some reproducibility issues (Youdim et al. Drug Metab. Dispos. 2007 February; 35 (2):275-282), but these lines are even further removed from native context and can give misleading results. Better methods are needed both in the research setting and in the market place.
Other public health related areas are also in need of improved methods for predicting effects in humans and animals including air quality, cosmetics, apparel, infant food, drinking water, environmental toxicology, food additives, nutraceuticals, manufacturing, organic foods, plastics, pesticides, industrial toxicity, toys, and waste water. Just about any area where exposure of potential toxins to humans or animals occurs is an area where improved method for detecting toxicological liabilities would be a benefit.